Abstract
This paper frames social machines as problem solving entities, demonstrating how their ecosystems address multiple stakeholders' problems. It enumerates aspects relevant to the theory and real-world practice of social machines, based on qualitative observations from our experiences building them. We frame evolving issues including: changing functionality, users, data and context; geographical and temporal scope (considering data granularity and visibility); and social scope. The latter is wide-ranging, including motivation, trust, experience, security, governance, control, provenance, privacy and law. We provide suggestions about building flexibility into social machines to allow for change, and defining social machines in terms of problems and stakeholders.
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